基于ROMS模式的南海SST与SSH四维变分同化研究

卫星遥感观测获得了大量高分辨率的海面实时信息，包括海面温度（SST）和海面高度（SSH）等，同化进入数值模式可有效提升模拟精度。本文基于ROMS模式与四维变分同化方法（4DVAR），使用AVHRR SST和AVISO SSH数据，开展了南海区域同化实验。为检验同化的效果，分别利用HYCOM再分析资料和Argo温盐实测数据分析了同化结果的海面高度、流场及温盐剖面的精度。对比结果表明，SST和SSH的同化能够改善ROMS的模拟结果:同化后海面高度场能够更为准确地捕捉海洋的中尺度特征，与HYCOM海面高度再分析资料相比，平均绝对偏差和均方根误差分别为0.054 m和0.066 m；与HYCOM 10 m层流场相比，东向与北向流速平均绝对偏差分别为0.12 m/s和0.11 m/s，相比未同化均提升约0.01 m/s；温盐同化结果与Argo温盐实测具有较高的一致性，温度和盐度平均绝对偏差为0.45℃、0.077，均方根误差为0.91℃、0.11，单个的温盐廓线对比说明，同化结果与HYCOM再分析资料精度相当。

4DVAR assimilation of SST and SSH data in South China Sea based on ROMS

Oceanic surface information with large scale, real-time, high resolution has been collected by satellite remote sensing instruments, including sea surface temperature (SST) and sea surface height (SSH), which could be assimilated in ocean model to enhance the simulation. In this paper, an experiment in South China Sea is conducted based on ROMS and 4DVAR method, by assimilating the AVHRR SST and AVISO sea level anomalies (SLA) data. To confirm the efficiency of the assimilation, the HYCOM reanalysis data and Argo in situ profile are applied to validate the SSH, current and temperature-salinity (T-S) field of the assimilation. The results show that the simulation is enhanced after the SST and SSH assimilation. The capability of mesoscale characteristics detection in SSH outcomes is promoted, and the absolute bias (Abias) and root mean square error (RMSE) are 0.054 m and 0.066 m, compared with the HYCOM surface elevation. Considering the velocity evaluation with HYCOM, the averaged Abias of the eastward and northward velocity at 10 m layer is 0.12 m/s and 0.011 m/s, accompanied with a promotion of 0.01 m/s. Meanwhile, the assimilation results agree with the Argo T-S profiles well, the averaged Abias of T-S is 0.45℃, 0.077, while the RMSE is 0.91℃ and 0.11, respectively. Moreover, the analysis of single T-S profile indicates that the assimilation results achieve a comparable accuracy with HYCOM.